Method for reducing artifacts in a spatial measurement

ABSTRACT

A method for artifact reduction in sonomicrometer obtained intracranial pressure measurements generally comprises isolating a component of a sonomicrometer waveform attributable solely to changes in intracranial volume by using a neural network or other nonlinear engine to extract a heartbeat component from the sonomicrometer output. Because the heartbeat is so characteristic, no actual measurement of the heartbeat as the forcing function is required to isolate the resulting changes in distance from the artifact induced changes in distance. The neural network then be utilized to directly map measured changes in skull distance over time to changes in intracranial pressure over a volume change, the inverse of compliance. The method is generally extendable to use with other volumetric based measurement techniques.

RELATED APPLICATION INFORMATION

This application is a continuation of our application Ser. No.09/780,767 entitled METHOD FOR ARTIFACT REDUCTION IN INTRACRANIALPRESSURE MEASUREMENTS filed Feb. 9, 2001 now U.S. Pat. No. 6,682,491,which is incorporated herein by reference, and claims priority toprovisional application Ser. No. 60/181,731, filed Feb. 11, 2000.

FIELD OF THE INVENTION

The present invention relates to artifact reduction. More particularly,the invention relates to a method for reducing artifacts in a spatialmeasurement.

BACKGROUND

It is known that a relative measure of intracranial pressure may benon-invasively obtained by measuring changes in a patient's skulldiameter with a sonomicrometer or similar volumetric measurement typedevice. According to the known method, changes in the patient's skulldiameter are directly related to changes in the patient's intracranialpressure. Because, however, the measured changes in skull diameter areextraordinarily small, indications of intracranial pressure obtainedthrough this method are highly subject to vibration and/or slow driftartifacts. While vibration artifacts, such as may result from touchingof the patient, may generally be removed from the estimate throughsimple low pass filtering, this is not the case for slow driftartifacts, such as may result from patient movements and the like. Slowdrift artifacts are generally indistinguishable in the frequency domainfrom changes in intracranial pressure caused by edema, infectiousprocess, tumor growth or bleeding. As a result, slow drift artifacts aregenerally very difficult to remove through standard filteringtechniques.

It is therefore a primary object of the present invention to improveover the prior art by providing a method whereby slow drift typeartifacts may be eliminated from the sonomicrometer obtained signals,thereby improving the quality of intracranial pressure measurement dataderived therefrom. Although those of ordinary skill in the art willrecognize that one such means for accomplishing this objective involvessecuring the sonomicrometer to the patient's skull with bone screws orthe like, such a solution completely destroys the sonomicrometer'snon-invasive character. As a result, it is a further object of thepresent invention to meet the primary object without sacrifice of theoverall technique's non-invasive character.

SUMMARY OF THE INVENTION

In accordance with the foregoing objects, the present invention—a methodfor artifact reduction in sonomicrometer obtained intracranial pressuremeasurements—generally comprises isolating a component of asonomicrometer waveform attributable solely to changes in intracranialvolume by using a neural network or other nonlinear engine to extract aheartbeat component from the sonomicrometer output. Because theheartbeat is so characteristic, no actual measurement of the heartbeatas the forcing function is required to isolate the resulting changes indistance from the artifact induced changes in distance. The neuralnetwork can then be utilized to directly map measured changes in skulldistance over time to changes in intracranial pressure over a volumechange, the inverse of compliance.

According to the present invention a mapping from the sonomicrometerobtained distance measurements to an index of the mean intracranialpressure is obtained by using a neural network to examine only thosecomponents of the distance measurements corresponding to a known forcingfunction. According to the preferred implementation function, the knownforcing function is chosen to be the heart beat waveform—awell-documented and highly characteristic waveform. By examining onlythose distance changes associated with the heart beat forcing function,artifacts associated with patient movement and the like are eliminatednotwithstanding the fact that they may have fundamental frequenciescorresponding to changes in intracranial pressure due to edema,infectious process, tumor growth and especially bleeding.

Finally, many other features, objects and advantages of the presentinvention will be apparent to those of ordinary skill in the relevantarts, especially in light of the foregoing discussions and the followingdrawings and exemplary detailed description.

BRIEF DESCRIPTION OF THE DRAWINGS

Although the scope of the present invention is much broader than anyparticular embodiment, a detailed description of the preferredembodiment follows together with illustrative figures, wherein likereference numerals refer to like components, and wherein:

FIG. 1 shows a known relationship between changes in intracranial volumeand intracranial pressure; and

FIG. 2 shows an implementation according to the present invention forextracting a measure of intracranial compliance from a sonomicrometeroutput.

DETAILED DESCRIPTION

Although those of ordinary skill in the art will readily recognize manyalternative embodiments, especially in light of the illustrationsprovided herein, this detailed description is exemplary of the preferredembodiment of the present invention, the scope of which is limited onlyby the claims which may be drawn hereto.

It is known that increases in intracranial pressure are normallybuffered by the displacement of blood and cerebrospinal fluid from thecranium when there is an increase in intracranial volume, such as fromedema, infectious process, tumor growth, bleeding or the like. Thisdisplacement, however, is limited by the total compliance of the boneand tissue forming the cranium. As depicted in the elastance curve ofFIG. 1, as the intracranial volume approaches the capacity of thecranium, the compliance of the bone and tissue decreases and theintracranial pressure rises at an increasingly greater rate. Consideringthis relationship in reverse, therefore, it may be postulated that asthe mean intracranial pressure increases, the effect on cranialcompliance of a change in intracranial volume will be less and lessprofound. As a result, if a component of a sonomicrometer obtaineddistance waveform can be isolated from the artifacts within the waveformand attributed solely to a change in intracranial volume, then thatisolated component may be relied upon as the basis for a measure ofcranial compliance. Although not an absolute measure of intracranialpressure, the resulting compliance index can nonetheless be a veryuseful relative measure of the patient's physiology.

Referring now to FIG. 2, there is shown depicted one such means forisolating a component of a sonomicrometer waveform attributable solelyto changes in intracranial volume. According to the method of thepresent invention, neural network or other nonlinear engine is used toextract a heartbeat component from the sonomicrometer output. Becausethe heartbeat is so characteristic, no actual measurement of theheartbeat as the forcing function is required to isolate the resultingchanges in distance from the artifact induced changes in distance. Aneural network, or the like, may be implemented to directly map measuredchanges in skull distance over time to changes in intracranial pressureover a volume change, the inverse of compliance.

Further, it is thought that the resulting compliance index mayeventually be mapped to absolute measures of mean intracranial pressureaccording to key indicators to be discovered in the compliance indexwaveform. In particular, because the compliance index is a function ofintracranial pressure, intracranial pressure may be estimated based upona measured compliance index. The end result is an estimate ofintracranial pressure derived from pulsatile changes in skull dimensionand the knowledge of the intracranial pressure to compliance indexrelationship.

While the foregoing description is exemplary of the preferred embodimentof the present invention, those of ordinary skill in the relevant artswill recognize the many variations, alterations, modifications,substitutions and the like as are readily possible, especially in lightof this description and the accompanying drawings. In any case, becausethe scope of the present invention is much broader than any particularembodiment, the foregoing detailed description should not be construedas a limitation of the scope of the present invention, which is limitedonly by the claims that may be drawn hereto.

1. A method of artifact reduction in intracranial pressure measurementscomprising isolating the change in distance attributable to changes inintracranial volume by extracting a heartbeat component from themeasurements utilizing a neural network to map measured changes in skulldistance over time.
 2. The method according to claim 1 wherein changesin intracranial pressure over time are compared to changes in skulldistance.
 3. A method of artifact reduction in a spatial measurement ofa cranium, comprising the steps of: isolating a first component of thespatial measurement from a second, artifact-induced component of thespatial measurement by extracting components of the spatial measurementthat correspond to a heart beat waveform; and mapping measured changesin skull distance over time to changes in intracranial pressure over avolume change.
 4. The method of claim 3, wherein a neural network isused to isolate the first component from the second, artifact-inducedcomponent.